Six solutions for more reliable infant research
Six solutions for more reliable infant research
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DOI：
10.1002/icd.2296
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发表时间：
2021-12-29
影响因子：
2.2
通讯作者：
Savalei, Victoria
中科院分区：
文献类型：
--
作者：
Byers-Heinlein, Krista;Bergmann, Christina;Savalei, Victoria
婴儿研究往往缺乏动力，破坏了我们研究结果的稳健性和可重复性。提高婴儿研究的可靠性为增加独立于样本量的统计能力提供了一个解决方案。在这里，我们讨论两种意义上的术语的可靠性在婴儿研究的背景下：可靠（大）的影响和可靠的措施。我们研究了效应最强和测量最可靠的情况，并使用合成数据集来说明效应大小、测量可靠性和统计能力之间的关系。然后，我们提出了六个具体的解决方案，以提高婴儿研究的可靠性：(a)定期估计和报告婴儿任务的效应大小和测量可靠性，(b)选择最佳测量工具，(c)开发更好的婴儿范式，(d)收集每个婴儿更多的数据点，(e)从分析中排除不可靠的数据，以及(f)进行更复杂的数据分析。在婴儿研究中更深入地考虑测量将提高我们研究婴儿发育的能力。
Infant research is often underpowered, undermining the robustness and replicability of our findings. Improving the reliability of infant studies offers a solution for increasing statistical power independent of sample size. Here, we discuss two senses of the term reliability in the context of infant research: reliable (large) effects and reliable measures. We examine the circumstances under which effects are strongest and measures are most reliable and use synthetic datasets to illustrate the relationship between effect size, measurement reliability, and statistical power. We then present six concrete solutions for more reliable infant research: (a) routinely estimating and reporting the effect size and measurement reliability of infant tasks, (b) selecting the best measurement tool, (c) developing better infant paradigms, (d) collecting more data points per infant, (e) excluding unreliable data from the analysis, and (f) conducting more sophisticated data analyses. Deeper consideration of measurement in infant research will improve our ability to study infant development.